mvpa2.misc.data_generators

Miscellaneous data generators for unittests and demos

Functions

autocorrelated_noise(ds, sr, cutoff[, lfnl, ...])	Generate a dataset with samples being temporally autocorrelated noise.
chirp_linear(n_instances[, n_features, ...])	Generates simple dataset for linear regressions
double_gamma_hrf(t[, A1, W1, K1, A2, W2, K2])	Hemodynamic response function model.
dumb_feature_binary_dataset()	Very simple binary (2 labels) dataset
dumb_feature_dataset()	Create a very simple dataset with 2 features and 3 labels
get_mv_pattern(s2n)	Simple multivariate dataset
get_random_rotation(ns[, nt, data])	Return some random rotation (or rotation + dim reduction) matrix
linear1d_gaussian_noise([size, slope, ...])	A straight line with some Gaussian noise.
linear_awgn([size, intercept, slope, ...])	Generate a dataset from a linear function with AWGN (Added White Gaussian Noise).
multiple_chunks(func, n_chunks, *args, **kwargs)	Replicate datasets multiple times raising different chunks
noisy_2d_fx(size_per_fx, dfx, sfx, center[, ...])	Yet another generator of random dataset
normal_feature_dataset([perlabel, nlabels, ...])	Generate a univariate dataset with normal noise and specified means.
pure_multivariate_signal(patterns[, ...])	Create a 2d dataset with a clear purely multivariate signal.
random_affine_transformation(ds[, ...])	Distort a dataset by random scale, shift, and rotation.
simple_hrf_dataset([events, hrf_gen, ...])	events: list of Events or ndarray of onsets for simple(r) designs
sin_modulated(n_instances, n_features[, ...])	Generate a (quite) complex multidimensional non-linear dataset
single_gamma_hrf(t[, A, W, K])	Hemodynamic response function model.
vstack(datasets[, a])	Stacks datasets vertically (appending samples).
wr1996([size])	Generate ‘6d robot arm’ dataset (Williams and Rasmussen 1996)

Classes

Dataset(samples[, sa, fa, a])	Generic storage class for datasets with multiple attributes.
Event(**kwargs)	Simple class to define properties of an event.